Dynamic Real-Time Resource Provisioning for Massively Multiplayer Online Games

Abstract

Massively Multiplayer Online Games (MMOG) are a class of computationally-intensive client-server applications with severe real-time Quality of Service (QoS) requirements, such the number of updates per second each client needs to receive from the servers for a fluent and realistic experience. To guarantee the QoS requirements, game providers currently over-provision a large amount of their resources, which makes the overall efficiency of provisioning and utilisation of resources rather low and prohibits any but the largest providers from joining the market.To address this deficiency, we propose a new prediction-based method for dynamic resource provisioning and scaling of MMOGs in distributed Grid environments. Firstly, a load prediction service anticipates the future game world entity distribution from historical trace data using a fast and flexible neural network-based method. On top of it, we developed generic analytical game load models used to foresee future hot-spots that congest the game servers and make the overall environment fragmented and unplayable. Finally, a resource allocation service performs dynamic load distribution, balancing, and migration of entities that keep the game servers reasonably loaded such that the real-time QoS requirements are maintained.KeywordsGame WorldGame SessionGame ServerFirst Person ShooterGame ProviderThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.